ESA WorldCover 2020

The European Space Agency (ESA) WorldCover product provides a global land cover map for 2020 at 10 m resolution based on Sentinel-1 and Sentinel-2 data.

Dataset Description

The European Space Agency (ESA) WorldCover product provides a global land cover map for 2020 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of the ESA WorldCover project, part of the 5th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency.


Users should keep in mind that the WorldCover map is a global-scale dataset, generated with a single methodology applied over all regions. As such, the accuracy of the map may vary between locations and with scale. That said, a crucial aspect for WorldCover was the involvement of several end users active in different domains who provided primary input for all engineering aspects and followed the whole project workflow from design up to validation and uptake. Consequently, WorldCover intends to provide a substantial benefit to various user communities and expands the established global land cover base of users and the development of novel services.


The methodology applied to generate the WorldCover global land cover product builds further on the algorithm used to generate the dynamic yearly Copernicus Global Land Service Land Cover (CGLS-LC) map at 100 m resolution (Buchhorn et al., 2020). The CGLS-LC workflow uses 100 m, 5-day, Proba-V data as an input which were re-processed to the Sentinel-2 UTM grid together with training data obtained at 10 m resolution. For the generation of the WorldCover map however both Sentinel-2 multi-spectral image data and Sentinel-1 C-band Synthetic Aperture Radar (SAR) data are used instead of Proba-V data.

The following methodological steps were included in the production of the WorldCover map:

  • Level 2A (L2A) and Ground Range Detected (GRD) products for Sentinel-2 (S2) and Sentinel-1 (S1) respectively, are selected and either filtered for cloud cover (Sentinel-2) or pre-processed to Gamma0 backscatter time series (for Sentinel-1).
  • Clouds and, cloud shadows are removed in the Sentinel-2 reflectance bands. Median composites are computed from the cleaned band time series and additional vegetation indices (VI) for each time series step are calculated. For S1 bands, an additional multitemporal speckle filter is used before compositing the timeseries.
  • Starting from those cleaned time series, temporal descriptive statistics are computed as well as 6 averaged timestamps. These are used as features together with some additional features extracted from auxiliary layers (e.g. the Copernicus Global Digital Elevation Model) in the classification.
  • Next, different models (scenarios) are trained with a gradient boosting decision tree algorithm (CatBoost) using a manually labelled set of training data at 10 m resolution available from the Copernicus Global Land Service Land Cover, complemented with training data obtained from OpenStreetMap, Global Surface Water Explorer and Global Mangrove Watch.
  • Finally, the probabilities of the different scenarios are improved with the help of several auxiliary datasets (OpenStreetMap, Global Surface Water Explorer, Global Mangrove Watch, World Settlement Footprint) into a final Land Cover map.

Uncertainty and Accuracy

The Worldcover data are assessed using an independent statistical accuracy assessment, map comparisons, spatial accuracy assessment and end-user assessments. The statistical accuracy assessment follows the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) Land Product Validation (LPV) requirements. A global stratification independent of any land cover map and using the Sentinel 2 Universal Transverse Mercator (UTM) grid as a geographic base has been applied to provide more than 21,000 primary sampling units (PSUs) with each containing one hundred 10x10 m reference pixels for the years 2020 - for robust accuracy assessment at global and continental levels (minimum of 3000 PSUs per continent).

Dataset Sustainment

The Worldcover dataset is demonstration product from the European Space Agency and is expected to migrate to the operational Copernicus global land cover monitoring service in the coming years.

Technical Characteristics

Spatial resolution: 1°/12000 or (~10 m)

Geographical coverage: Global

Temporal coverage: 2020

Update frequency: Annual

Format: GeoTIFF

Data Policy: Creative Commons Attribution 4.0 International (CC-BY-4.0)

Associated Guidance or User Manual

Product manual not yet available (October 2021), but it will be available from:

Validation report not yet available (October 2021), but it will be available from:

Dataset link not yet available (October 2021), but it will be available from:

Points of contact for queries

Ruben Van De Kerchove
WorldCover Project Manager
Flemish Institute for Technological Research (VITO)
Mol, Belgium

Olivier Arino
WorldCover Technical Officer
European Space Agency
Frascati, Italy